5Development of a Multi-objective Salp Swarm Algorithm for Benchmark Functions and Real-world Problems
The salp swarm algorithm is a recent optimization technique. This algorithm is a swarm-based nature-inspired algorithm, which emulates and scientifically models the conduct of salp chains in the remote ocean. The proposed calculation can be used for managing linear and nonlinear optimization problems. The salp swarm algorithm (SSA) and the multi-target salp swarm algorithm (MSSA) have made progress towards various benchmark test capacities to aid and demonstrate the execution of the algorithm. Results from the SSA are compared with genuine esteems of the test functions, and results from the MSSA are compared with those of other multi-objective algorithms. For obtaining solutions of constrained test functions, the constraints handling technique is employed to transform the constrained optimization problem into an unconstrained optimization problem for which the interior penalty method is used. The algorithm is successfully applied to a cantilever beam, which is the practical designing problem, and compared with the results of NSGA-II. The obtained results converge and are nearer to an optimum solution in comparison with NSGA-II.
5.1. Introduction
Optimization is known as the way to deal with discovering ideal course of action under given conditions. In design problems, engineers need to take a few administrative and specific decisions at different stages. A definitive objective ...